SoroushVahidi/scidocs huggingface dataset:
Formal Models for Computer Security
(1981)

Efforts to build "secure" computer systems have now been underway for more than a decade. Many designs have been proposed, some prototypes have been constructed, and a few systems are approaching the production stage. A small number of systems are even operating in what the Department of Defense calls the "multilevel" mode some information contained m these computer systems may have a clasmfication higher than the clearance of some of the users of those systems. This paper revmws the need for formal security models, describes the structure and operation of military security controls, considers how automation has affected security problems, surveys models that have been proposed and applied to date, and suggests possible d~rectlons for future models
The Cerebellum, Sensitive Periods, and Autism
(2014)

Cerebellar research has focused principally on adult motor function. However, the cerebellum also maintains abundant connections with nonmotor brain regions throughout postnatal life. Here we review evidence that the cerebellum may guide the maturation of remote nonmotor neural circuitry and influence cognitive development, with a focus on its relationship with autism. Specific cerebellar zones influence neocortical substrates for social interaction, and we propose that sensitive-period disruption of such internal brain communication can account for autism's key features.
Configuration Tool for ARINC 653 Operating Systems Eu
(2014)

ARINC 653 Specification defines a standardized interface of real-time operating systems and an Application Executive (APEX) to develop the reliable applications for avionics based on Integrated Modular Avionics (IMA). The requirements of system platform based on ARINC 653 Standard are defined as configuration data and are integrated to the XML configuration file(s) in the real-time operating system. Unfortunately, existing configuration tools for integrating requirements do not provide checking the syntax errors of XML and verifying the integrity of input data for partitioning. This paper presents a configuration tool for ARINC 653 OS that consist of Wizard module which generates the basic configuration data for IMA based on XML Scheme of ARINC 653 Standard, XML and Partition Editor for the partitioning system of IMA, and Verification module which checks the integrity of input data and XML syntax with its visualization.
Energy and Performance Characterization of Mobile Heterogeneous Computing
(2012)

A modern mobile application processor is a heterogeneous multi-core SoC which integrates CPU and application-specific accelerators such as GPU and DSP. It provides opportunity to accelerate other compute-intensive applications, yet mapping an algorithm to such a heterogeneous platform is not a straightforward task and has many design decisions to make. In this paper, we evaluate the performance and energy benefits of utilizing the integrated GPU and DSP cores to offload or share CPU's compute-intensive tasks. The evaluation is conducted on three representative mobile platforms, TI's OMAP3530, Qualcomn's Snapdragon S2, and Nvidia's Tegra2, using common computation tasks in mobile applications. We identify key factors that should be considered in energy-optimized mobile heterogeneous computing. Our evaluation results show that, by effectively utilizing all the computing cores concurrently, an average of 3.7X performance improvement can be achieved with the cost of 33% more power consumption, in comparison with the case of utilizing CPU only. This stands for 2.8X energy saving.
Scene Text Synthesis for Efficient and Effective Deep Network Training
(2019)

A large amount of annotated training images is critical for training accurate and robust deep network models but the collection of a large amount of annotated training images is often time-consuming and costly. Image synthesis alleviates this constraint by generating annotated training images automatically by machines which has attracted increasing interest in the recent deep learning research. We develop an innovative image synthesis technique that composes annotated training images by realistically embedding foreground objects of interest (OOI) into background images. The proposed technique consists of two key components that in principle boost the usefulness of the synthesized images in deep network training. The first is context-aware semantic coherence which ensures that the OOI are placed around semantically coherent regions within the background image. The second is harmonious appearance adaptation which ensures that the embedded OOI are agreeable to the surrounding background from both geometry alignment and appearance realism. The proposed technique has been evaluated over two related but very different computer vision challenges, namely, scene text detection and scene text recognition. Experiments over a number of public datasets demonstrate the effectiveness of our proposed image synthesis technique the use of our synthesized images in deep network training is capable of achieving similar or even better scene text detection and scene text recognition performance as compared with using real images.
A Novel CPW Fed Multiband Circular Microstrip Patch Antenna for Wireless Applications
(2012)

In this paper, a novel design of coplanar micro strip patch antenna is presented for ultra wideband (UWB) and smart grid applications. It is designed on a dielectric substrate and fed by a coplanar wave guide (CPW). Micro strip patch antenna consists of a circular patch with an elliptical shaped eye opening in the center to provide multiband operations. The antenna has wide bandwidth of 5 GHz between 10.8-15.8 GHz and 3 GHz between 5.8-8.8 GHz, high return loss of -34 dB at 3.9 GHz and -29 dB at 6.8 GHz with satisfactory radiation properties. The parameters that affect the performance of the antenna in terms of its frequency domain characteristics are investigated. The antenna design has been simulated on Ansoft's High Frequency Structure Simulator (HFSS). It is a compact design of 47 × 47 mm2 area on Rogers RO3003 (tm) substrate with dielectric constant of 3 and thickness of 1.6 mm. The simulated antenna has three operating frequency bands at 2.82, 5.82-8.8, 10.8-15.8 GHz and shows the band-notch characteristic in the UWB band to avoid interferences, which is caused by WLAN at 5.15-5.825 GHz and Wi-MAX at 5.25-5.85 GHz. The designed antenna structure with 5.68 dBi gain is planar, simple and compact, hence it can be easily embedded in wireless communication systems and integrated with microwave circuitry for low manufacturing cost.
Majority is not enough: bitcoin mining is vulnerable
(2014)

The Bitcoin cryptocurrency records its transactions in a public log called the blockchain. Its security rests critically on the distributed protocol that maintains the blockchain, run by participants called miners. Conventional wisdom asserts that the mining protocol is incentive-compatible and secure against colluding minority groups, that is, it incentivizes miners to follow the protocol as prescribed.
 We show that the Bitcoin mining protocol is not incentive-compatible. We present an attack with which colluding miners' revenue is larger than their fair share. The attack can have significant consequences for Bitcoin: Rational miners will prefer to join the attackers, and the colluding group will increase in size until it becomes a majority. At this point, the Bitcoin system ceases to be a decentralized currency.
 Unless certain assumptions are made, selfish mining may be feasible for any coalition size of colluding miners. We propose a practical modification to the Bitcoin protocol that protects Bitcoin in the general case. It prohibits selfish mining by a coalition that command less than 1/4 of the resources. This threshold is lower than the wrongly assumed 1/2 bound, but better than the current reality where a coalition of any size can compromise the system.
Containers and Virtual Machines at Scale: A Comparative Study
(2016)

Virtualization is used in data center and cloud environments to decouple applications from the hardware they run on. Hardware virtualization and operating system level virtualization are two prominent technologies that enable this. Containers, which use OS virtualization, have recently surged in interest and deployment. In this paper, we study the differences between the two virtualization technologies. We compare containers and virtual machines in large data center environments along the dimensions of performance, manageability and software development.
 We evaluate the performance differences caused by the different virtualization technologies in data center environments where multiple applications are running on the same servers (multi-tenancy). Our results show that co-located applications can cause performance interference, and the degree of interference is higher in the case of containers for certain types of workloads. We also evaluate differences in the management frameworks which control deployment and orchestration of containers and VMs. We show how the different capabilities exposed by the two virtualization technologies can affect the management and development of applications. Lastly, we evaluate novel approaches which combine hardware and OS virtualization.
Path Planning and Steering Control for an Automatic Perpendicular Parking Assist System
(2015)

This paper considers the perpendicular reverse parking problem of front wheel steering vehicles. Relationships between the widths of the parking aisle and the parking place, as well as the parameters and initial position of the vehicle for planning a collision-free reverse perpendicular parking in one maneuver are first presented. Two types of steering controllers (bang-bang and saturated tanh-type controllers) for straightline tracking are proposed and evaluated. It is demonstrated that the saturated controller, which is continuous, achieves also quick steering avoiding chattering and can be successfully used in solving parking problems. Simulation results and first experimental tests confirm the effectiveness of the proposed control scheme.
A Low-Power Wideband Transmitter Front-End Chip for 80 GHz FMCW Radar Systems With Integrated 23 GHz Downconverter VCO
(2012)

A low-power FMCW 80 GHz radar transmitter front-end chip is presented, which was fabricated in a SiGe bipolar production technology ( fT=180 GHz, fmax=250 GHz ). Additionally to the fundamental 80 GHz VCO, a 4:1-frequency divider (up to 100 GHz), a 23 GHz local oscillator (VCO) with a low phase noise of -112 dBc/Hz (1 MHz offset), a PLL-mixer and a static frequency divider is integrated together with several output buffers. This chip was designed for low power consumption (in total <; 0.5 W, i.e., 100 mA at 5 V supply voltage), which is dominated by the 80 GHz VCO due to the demands for high output power (≈ 12 dBm) and low phase noise (minimum -97 dBc/Hz at 1 MHz offset) within the total wide tuning range from 68 GHz to 92.5 GHz (Δf = 24.5 GHz). Measurements of the double-PLL system at 80 GHz showed a low phase noise of -88 dBc/Hz at 10 kHz offset frequency.
Face Alignment Across Large Poses: A 3D Solution
(2016)

Face alignment, which fits a face model to an image and extracts the semantic meanings of facial pixels, has been an important topic in CV community. However, most algorithms are designed for faces in small to medium poses (below 45), lacking the ability to align faces in large poses up to 90. The challenges are three-fold: Firstly, the commonly used landmark-based face model assumes that all the landmarks are visible and is therefore not suitable for profile views. Secondly, the face appearance varies more dramatically across large poses, ranging from frontal view to profile view. Thirdly, labelling landmarks in large poses is extremely challenging since the invisible landmarks have to be guessed. In this paper, we propose a solution to the three problems in an new alignment framework, called 3D Dense Face Alignment (3DDFA), in which a dense 3D face model is fitted to the image via convolutional neutral network (CNN). We also propose a method to synthesize large-scale training samples in profile views to solve the third problem of data labelling. Experiments on the challenging AFLW database show that our approach achieves significant improvements over state-of-the-art methods.
Recommending Self-Regulated Learning Strategies Does Not Improve Performance in a MOOC
(2016)

Many committed learners struggle to achieve their goal of completing a Massive Open Online Course (MOOC). This work investigates self-regulated learning (SRL) in MOOCs and tests if encouraging the use of SRL strategies can improve course performance. We asked a group of 17 highly successful learners about their own strategies for how to succeed in a MOOC. Their responses were coded based on a SRL framework and synthesized into seven recommendations. In a randomized experiment, we evaluated the effect of providing those recommendations to learners in the same course (N = 653). Although most learners rated the study tips as very helpful, the intervention did not improve course persistence or achievement. Results suggest that a single SRL prompt at the beginning of the course provides insufficient support. Instead, embedding technological aids that adaptively support SRL throughout the course could better support learners in MOOCs.
ANMPI-BASED PARALLEL AND DISTRIBUTED MACHINE LEARNING PLATFORM ON LARGE-SCALE HPC CLUSTERS
(2012)

This paper presents the design of an MPI-based parallel and distributed machine learning platform on large-scale HPC clusters. Researchers and practitioners can implement easily a class of parallelizable machine learning algorithms on the platform, or port quickly an existing non-parallel implementation of a parallelizable algorithm to the platform with only minor modifications. Complicated functions in parallel programming such as scheduling, caching and load balancing are handled automatically by the platform. The platform performance was evaluated in a series of stress tests by using a k-means clustering task on 7,500 hours of speech data (about 2.7 billion 52dimensional feature vectors). Good scalability is demonstrated on an HPC cluster with thousands of CPU cores.
Stereo Acoustic Echo Cancellation Employing Frequency-Domain Preprocessing and Adaptive Filter
(2011)

This paper proposes a windowing frequency domain adaptive filter and an upsampling block transform preprocessing to solve the stereo acoustic echo cancellation problem. The proposed adaptive filter uses windowing functions with smooth cutoff property to reduce the spectral leakage during filter updating, so the utilization of the independent noise introduced by preprocessing in stereo acoustic echo cancellation can be increased. The proposed preprocessing is operated in short blocks with low processing delay, and it uses frequency-domain upsampling to meet the minimal block length requirement given by the band limit of simultaneous masking. Therefore, the simultaneous masking can be well utilized to improve the audio quality. The acoustic echo cancellation simulations and the audio quality evaluation show that, the proposed windowing frequency domain adaptive filter performs better than the conventional frequency domain adaptive filter in both mono and stereo cases, and the upsampling block transform preprocessing provides better audio quality and stereo acoustic echo cancellation performance than the half-wave preprocessing at the same noise level.
Spatial but not verbal cognitive deficits at age 3 years in persistently antisocial individuals.
(2002)

Previous studies have repeatedly shown verbal intelligence deficits in adolescent antisocial individuals, but it is not known whether these deficits are in place prior to kindergarten or, alternatively, whether they are acquired throughout childhood. This study assesses whether cognitive deficits occur as early as age 3 years and whether they are specific to persistently antisocial individuals. Verbal and spatial abilities were assessed at ages 3 and 11 years in 330 male and female children, while antisocial behavior was assessed at ages 8 and 17 years. Persistently antisocial individuals (N = 47) had spatial deficits in the absence of verbal deficits at age 3 years compared to comparisons (N = 133), and also spatial and verbal deficits at age 11 years. Age 3 spatial deficits were independent of social adversity, early hyperactivity, poor test motivation, poor test comprehension, and social discomfort during testing, and they were found in females as well as males. Findings suggest that early spatial deficits contribute to persistent antisocial behavior whereas verbal deficits are developmentally acquired. An early-starter model is proposed whereby early spatial impairments interfere with early bonding and attachment, reflect disrupted right hemisphere affect regulation and expression, and predispose to later persistent antisocial behavior.
Facile one-pot solvothermal method to synthesize sheet-on-sheet reduced graphene oxide (RGO)/ZnIn2S4 nanocomposites with superior photocatalytic performance.
(2014)

Highly reductive RGO (reduced graphene oxide)/ZnIn2S4 nanocomposites with a sheet-on-sheet morphology have been prepared via a facile one-pot solvothermal method in a mixture of N,N-dimethylformamide (DMF) and ethylene glycol (EG) as solvent. A reduction of GO (graphene oxide) to RGO and the formation of ZnIn2S4 nanosheets on highly reductive RGO has been simultaneously achieved. The effect of the solvents on the morphology of final products has been investigated and the formation mechanism was proposed. The as-prepared RGO/ZnIn2S4 nanoscomposites were characterized by powder X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FT-IR), Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), N2-adsorption BET surface area, UV-vis diffuse reflectance spectroscopy (DRS), scanning electron microscopy (SEM), transmission electron microscopy (TEM), high-resolution transmission electron microscopy (HRTEM). The photocatalytic activity for hydrogen evolution under visible light irradiations over the as-prepared RGO/ZnIn2S4 nanocomposites has been investigated. The as-prepared RGO/ZnIn2S4 nanocomposites show enhanced photocatalytic activity for hydrogen evolution under visible light irradiations and an optimum photocatalytic activity is observed over 1.0 wt % RGO incorporated ZnIn2S4 nanocomposite. The superior photocatalytic performance observed over RGO/ZnIn2S4 nanocomposites can be ascribed to the existence of highly reductive RGO which has strong interactions with ZnIn2S4 nanosheets. The existence of the strong interaction between ZnIn2S4 nanosheets and RGO in the nancomposites facilitates the electron transfer from ZnIn2S4 to RGO, with the latter serving as a good electron acceptor, mediator as well as the co-catalyst for hydrogen evolution. This study can provide some guidance for us in the developing of RGO-incorporated nanocomposite photocatalysts.
Improving optical character recognition through efficient multiple system alignment
(2009)

Individual optical character recognition (OCR) engines vary in the types of errors they commit in recognizing text, particularly poor quality text. By aligning the output of multiple OCR engines and taking advantage of the differences between them, the error rate based on the aligned lattice of recognized words is significantly lower than the individual OCR word error rates. This lattice error rate constitutes a lower bound among aligned alternatives from the OCR output. Results from a collection of poor quality mid-twentieth century typewritten documents demonstrate an average reduction of 55.0% in the error rate of the lattice of alternatives and a realized word error rate (WER) reduction of 35.8% in a dictionary-based selection process. As an important precursor, an innovative admissible heuristic for the A* algorithm is developed, which results in a significant reduction in state space exploration to identify all optimal alignments of the OCR text output, a necessary step toward the construction of the word hypothesis lattice. On average 0.0079% of the state space is explored to identify all optimal alignments of the documents.
RASR - The RWTH Aachen University Open Source Speech Recognition Toolkit
(2011)

RASR is the open source version of the well-proven speech recognition toolkit developed and used at RWTH Aachen University. The current version of the package includes state of the art speech recognition technology for acoustic model training and decoding. Speaker adaptation, speaker adaptive training, unsupervised training, discriminative training, lattice processing tools, flexible signal analysis, a finite state automata library, and an efficient dynamic network decoder are notable components. Comprehensive documentation, example setups for training and recognition, and tutorials are provided to support newcomers.
Properties and Therapeutic Application of Bromelain: A Review
(2012)

Bromelain belongs to a group of protein digesting enzymes obtained commercially from the fruit or stem of pineapple. Fruit bromelain and stem bromelainare prepared differently and they contain different enzymatic composition. "Bromelain" refers usually to the "stem bromelain." Bromelain is a mixture of different thiol endopeptidases and other components like phosphatase, glucosidase, peroxidase, cellulase, escharase, and several protease inhibitors. In vitro and in vivo studies demonstrate that bromelain exhibits various fibrinolytic, antiedematous, antithrombotic, and anti-inflammatory activities. Bromelain is considerably absorbable in the body without losing its proteolytic activity and without producing any major side effects. Bromelain accounts for many therapeutic benefits like the treatment of angina pectoris, bronchitis, sinusitis, surgical trauma, and thrombophlebitis, debridement of wounds, and enhanced absorption of drugs, particularly antibiotics. It also relieves osteoarthritis, diarrhea, and various cardiovascular disorders. Bromelain also possesses some anticancerous activities and promotes apoptotic cell death. This paper reviews the important properties and therapeutic applications of bromelain, along with the possible mode of action.
Light propagation with phase discontinuities: generalized laws of reflection and refraction.
(2011)

Conventional optical components rely on gradual phase shifts accumulated during light propagation to shape light beams. New degrees of freedom are attained by introducing abrupt phase changes over the scale of the wavelength. A two-dimensional array of optical resonators with spatially varying phase response and subwavelength separation can imprint such phase discontinuities on propagating light as it traverses the interface between two media. Anomalous reflection and refraction phenomena are observed in this regime in optically thin arrays of metallic antennas on silicon with a linear phase variation along the interface, which are in excellent agreement with generalized laws derived from Fermat's principle. Phase discontinuities provide great flexibility in the design of light beams, as illustrated by the generation of optical vortices through use of planar designer metallic interfaces.